Cumulative Fire Count (1950–2023)
Total Count
Counts how many times each 30 m pixel has burned between 1950 and 2023 across the western United States, based on authoritative wildfire perimeter and occurrence datasets.
About this dataset
This dataset shows how many times each location has burned over the past seven decades. Using authoritative wildfire perimeter and occurrence records for the western United States, we count the number of fires intersecting each 30-meter pixel from 1950 through 2023.
The resulting cumulative fire count surface highlights places with repeated burning, areas that have not burned in the modern record, and broad patterns of fire activity across states and ecoregions. These patterns can support fire history analysis, treatment planning, and communication about where fire has and has not returned to the landscape in recent decades.
This dataset is designed to be used alongside the companion wildfire severity layer derived from the Parks et al. method, which characterizes how severely those fires burned.
What’s included in this dataset
How to interpret this layer
This raster provides a pixel-level summary of wildfire history by counting the number of recorded fires that intersect each location. Analysts can use it to understand where repeated burning has occurred, compare fire activity across regions, or identify areas that have seen little to no fire in the modern record. The dataset pairs naturally with the Fire Severity layer to show not only how often places burn, but with what ecological effect.
Explore the full Data Story
To dive deeper into the methods, context, and example applications behind this dataset, explore the full VPDC Data Story that accompanies it.
See the full Data Story ⭢How to get Started:
- Explore the map: Zoom and pan to locate your area of interest. The tile grid outlines the spatial boundaries of the dataset.
- Select your tiles: Click one or more tiles to highlight them. Each tile corresponds to a geographic area you can download.
- Review & adjust: Use the checkboxes in the selection list to confirm or deselect tiles.
- Download your data: Click the "Download Data" button to bundle your selected tiles into a single ZIP file.
A few things to keep in mind:
- Download limitations: For best performance, please select no more than 20 tiles per download. Larger selections may slow your browser or cause issues.
- Need more coverage? No problem—just download in smaller batches. All tiles use the same folder structure, so you can easily merge them later in your GIS software for seamless regional analysis.
- Working at larger scales? For very large areas, contact us to discuss alternative delivery options.
Tiling grid: To keep downloads efficient and analysis straightforward, the dataset is organized into a fixed tiling grid. This approach prioritizes optimal file sizes and regional coverage for analytical workflows. While the grid follows standard geospatial conventions, it is not pixel-aligned to USGS ARD or other standardized grids.
Selected Data Tiles:
Download
Cumulative Fire Count (1950–2023)
Counts how many times each 30 m pixel has burned between 1950 and 2023 across the western United States, based on authoritative wildfire perimeter and occurrence datasets.
Direct Download (Full File) - HTTPS Link
Use this link to download the entire file directly to your local storage through the browser. This method is ideal for quick and easy access but requires sufficient local storage and bandwidth for the full download.
Download data:
Heading
Explore scenario data downloads
Use the filters, then click a group to reveal individual downloads.
Direct Access
Get hands-on access to this dataset using interactive notebooks. Choose between the Google Colab notebook for quick exploration in your browser or access the hosted Jupyter Notebooks via Binder or GitHub for more advanced workflows.
Direct access to the Google Collab notebook
Open and explore instantly
Click the button to the left to launch an interactive notebook directly in your browser. This pre-configured Colab notebook provides a quick and easy way to explore, visualize, and analyze the data—no setup required.
GitHub hosted Jupyter Notebooks
Flexible access for advanced workflows
Access the full collection of Jupyter Notebooks hosted on GitHub. These notebooks can be used on your local machine or via cloud platforms like Binder or Google Colaboratory, providing flexibility for more advanced customizations.
Licensing & Attribution
Licensed under Creative Commons Attribution–NonCommercial–ShareAlike 4.0 International (CC BY-NC-SA 4.0).
You may share and adapt this dataset for noncommercial purposes with attribution under the same license.
Required Attribution:
© 2025 Vibrant Planet. Distributed by Vibrant Planet Data Commons. Licensed under CC BY-NC-SA 4.0.
For commercial or special-use requests, email us at contact@vpdatacommons.org
Disclaimer
Vibrant Planet provides the information hosted on the Vibrant Planet Data Commons site (www.vpdatacommons.org) (the “Site”) as a PUBLIC SERVICE for NONCOMMERCIAL USES only. The information is provided as-is, as-available, and without warranty of any kind, whether express, implied, or statutory, concerning the accuracy, completeness, reliability, or suitability of the information. Further, we do not warrant that this site will (i) be uninterrupted or error-free; or (ii) result in any desired outcome. We are not responsible for content of other services, data or public information that may be used by or linked to this site. By accessing this website and/or the data contained within, you assume the entire responsibility and liability related to the use of the information it contains, and you release Vibrant Planet Data Commons, Vibrant Planet and all data providers from liability. You may use the Site only for lawful purposes Users also should note that property boundaries included on any map do not represent an on-the-ground survey suitable for legal, engineering, or surveying purposes. They represent only the approximate relative locations. We reserve the right to withdraw or amend this Site, and any service or material we provide on the Site, in our sole discretion without notice. We will not be liable if for any reason all or any part of the Site is unavailable at any time or for any period. From time to time, we may restrict access to some parts of the Site, or the entire Site to users or visitors to the site. The Site and its entire contents, features, and functionality (including but not limited to all information, software, text, displays, images, video, and audio, and the design, selection, and arrangement thereof) are owned by Vibrant Planet Data Commons, its licensors, or other providers of such material and are protected by United States and international copyright, trademark, patent, trade secret, and other intellectual property or proprietary rights laws. This site is operated by Vibrant Planet Data Commons.